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Using Transport Activity-Based Model to Simulate the Pandemic

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  • Moez Kilani

    (ULCO - Université du Littoral Côte d'Opale, LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Ousmane Diop

    (ULCO - Université du Littoral Côte d'Opale, LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Ngagne Diop

    (ULCO - Université du Littoral Côte d'Opale, TVES - Territoires, Villes, Environnement & Société - ULR 4477 - ULCO - Université du Littoral Côte d'Opale - Université de Lille)

Abstract

We use an activity-based transport model to simulate the progression of a virus at the regional scale. We analyse several scenarios corresponding to distinct situations and describing how small initial clusters of infected agents expand and reach a pandemic level. We evaluate the effectiveness of some public restrictions and compare the number of infections with respect to the base-case scenario, where no restrictions are in place. We consider the wearing of masks in public transport and/or in some activities (work, leisure and shopping) and the implementation of a lockdown. Our analysis shows that education, including the primary level, is one of the major activities where infections occur. We find that the wearing of masks in transportation only does not yield important impacts. The lockdown is efficient in containing the spread of the virus but, at the same time, significantly increases the length of the wave (factor of two). This is because the number of agents who are susceptible to be infected remains high. Our analysis uses the murdasp tool specifically designed to process the output of transport models and performs the simulation of the pandemic.

Suggested Citation

  • Moez Kilani & Ousmane Diop & Ngagne Diop, 2023. "Using Transport Activity-Based Model to Simulate the Pandemic," Post-Print hal-03946166, HAL.
    • Handle: RePEc:hal:journl:hal-03946166
    DOI: 10.3390/su1010000
    Note: View the original document on HAL open archive server: https://hal.science/hal-03946166
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    References listed on IDEAS

    as
    1. Moez Kilani & Ngagne Diop & Daniel De Wolf, 2022. "A Multimodal Transport Model to Evaluate Transport Policies in the North of France," Sustainability, MDPI, vol. 14(3), pages 1-16, January.
    2. Sabina Saccomanno & Mauro Bernabei & Fabio Scoppa & Alessio Pirino & Rodolfo Mastrapasqua & Marina Angela Visco, 2020. "Coronavirus Lockdown as a Major Life Stressor: Does It Affect TMD Symptoms?," IJERPH, MDPI, vol. 17(23), pages 1-13, November.
    3. Richard Arnott & Moez Kilani, 2022. "Social Optimum in the Basic Bathtub Model," Transportation Science, INFORMS, vol. 56(6), pages 1505-1529, November.
    4. David Adam, 2020. "Simulating the pandemic: What COVID forecasters can learn from climate models," Nature, Nature, vol. 587(7835), pages 533-534, November.
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    Cited by:

    1. Harshana Weligampola & Lakshitha Ramanayake & Yasiru Ranasinghe & Gayanthi Ilangarathna & Neranjan Senarath & Bhagya Samarakoon & Roshan Godaliyadda & Vijitha Herath & Parakrama Ekanayake & Janaka Eka, 2023. "Pandemic Simulator: An Agent-Based Framework with Human Behavior Modeling for Pandemic-Impact Assessment to Build Sustainable Communities," Sustainability, MDPI, vol. 15(14), pages 1-26, July.

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